International Mammalian Genome Society

The 16th International Mouse Genome Conference (2002)

Oral Presentation

Monday 18 November

20:00 - 20:15 HRS


EJ Chesler
University of Tennessee Health Science Center,  University of Illinois at Urbana Champaign

Co-Authors 2) Rodriguez-Zas SL 1) Williams RW, 3) Mogil JS
Institutions: 1) University of Tennessee Health Science Center, 2) University of Illinois at Urbana-Champaign 3) McGill University, Dept. of Psychology University of Illinois at Urbana-Champaign

The possibility of performing “in silico” mapping of complex traits from the strain allelic distribution patterns of inbred mouse SNPs  (Grupe et al, 2001) has been hailed as an interesting advance in complex trait mapping.  However, concerns have been raised about the arbitrary nature of peak detection employed in this method, the redundant use of data from a limited number of strains, the high rate of false positive results, and the impact of inclusion of outlier strains (Chesler et al, 2001).  Empirical evaluation of this method is complicated by the fact that more genetic diversity is accounted for in a panel of standard inbred strains than in a typical mapping panel, often derived from only two progenitor lines.   Statistical methods of peak detection, including permutation resampling of trait data perform slightly better than the arbitrary thresholds for peak detection initially proposed by Grupe et al (2001), and allow users to make informed decisions regarding the control of error rate.  However, a major concern for use of this method is that it appears to rely on differences between single phenotypic outlier strains and the remainder of a strain panel.  While this generates rapid and useful identification of candidate loci, a high rate of false positives occur, and results remain limited to polymorphisms occurring in a single strain of mouse relative to other strains.  Thus, trait relevant loci will be identified using this method (with many false positives) but the true genetic variation in the overall population may not be correctly characterized.

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